The Computations of the Composing Brain: Cross-modal Generality and Computational Specificity

创作大脑的计算：跨模态通用性和计算特异性

• 批准号: 1221723
• 负责人: Liina Pylkkanen
• 金额: $ 44.5万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-15 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1221723&HistoricalAwards=false
• 关键词: Computations; Composing; Brain; Cross; modal

One of the most impressive aspects of human cognition is our ability to produce and comprehend an infinite range of expressions, built from a finite set of lexical items in our long-term memory. Although composition is a defining characteristic of human language, its neurobiology is still largely uncharacterized. Specifically, current models lack computational detail as to the specific functions executed by various "combinatory brain regions." Consequently, rehabilitation strategies for brain damaged individuals suffering sentence processing problems are similarly generic, not targeting specific computations. Second, while composition during comprehension has been studied for decades, we know almost nothing about composition in language production, mostly due to methodological reasons: movement artifacts during talking compromise almost every type of brain data. With funding from the National Science Foundation, Dr. Liina Pylkkänen and her research team will carry out the first comprehensive investigation of the neurobiology of linguistic composition that simultaneously strives both for computational specificity, assessing specific functional hypotheses emerging from theoretical linguistics, as well as cross-modal generality, systematically testing the same stimuli across both comprehension and production. To overcome the methodological hurdles of studying production, this research uses short combinatory expressions (e.g., 'grey cat' or 'eats meat'), which can be fully planned before articulation commences. Brain activity will be monitored millisecond by millisecond during this artifact-free planning stage with magnetoencephalography, which offers an unparalleled combination of spatial and temporal resolution. This project primarily uses a very simple word-picture matching task, which is easy enough for future application in clinical populations and children. A specific focus of this work is the computations of the left anterior temporal lobe (LATL), a brain region that is atrophied in semantic dementia, a degenerative disease characterized by loss of semantic memory. The project will investigate whether the roles of the LATL in composition on the one hand, and in semantic memory on the other, are neurally distinct or instances of a unified process of semantic specification. These findings could be transformative for our understanding of both composition and semantic memory, in the healthy brain as well as in dementia.

人类认知最令人印象深刻的方面之一是我们能够产生和理解无限范围的表达式，这是由我们长期记忆中的一组有限的词汇项目构建的。尽管组成是人类语言的定义特征，但其神经生物学仍然很大程度上没有特征。具体而言，当前模型缺乏有关各种“组合性大脑区域”执行的特定功能的计算细节。因此，遭受句子处理问题的大脑损坏的人的康复策略同样是通用的，而不是针对特定的计算。其次，尽管在理解过程中已经研究了数十年的理解，但我们几乎对语言生产中的构成一无所知，主要是由于方法论原因：在谈话过程中的运动伪影几乎每种类型的大脑数据。借助国家科学基金会的资助，LiinaPylkkänen博士和她的研究团队将对语言组成的神经生物学进行首次全面调查，这些调查仅仅努力取得了计算特异性，评估了从理论语言学出现的特定功能假设，以及跨模型的生成性，以及系统地测试跨性别的刺激性和跨性别刺激。为了克服研究生产的方法论障碍，该研究使用短的组合表达式（例如“灰猫”或“饮食肉”），在此无磁脑电图的无文物计划阶段中，将通过毫秒毫秒来监测大脑活动，这提供了磁脑摄影，这提供了空间和临时分辨率的无与伦比的组合。该项目主要采用非常简单的单词画面匹配任务，这对于将来在临床人群和儿童中的应用非常容易。这项工作的一个特定重点是左前临时叶（LATL）的计算，这是一种在语义痴呆症中受到萎缩的大脑区域，这是一种退化性疾病，其特征是语义记忆的丧失。该项目将研究LATL在组成中的作用是一方面的，另一方面是语义记忆中的作用是自然不同的还是统一的语义规范过程的实例。这些发现可能是我们对健康大脑以及痴呆症中构图和语义记忆的理解的变革性的。